Linguistic annotations (e.g., semantic role labeling (SRL), etc.) has proven crucial to understanding natural languages. Semantic role labeling is the task of automatically labeling predicates and arguments in a sentence with shallow semantic labels. Analyzing sentences in the form of predicates and arguments provides a more stable semantic representation across syntactically different sentences, thereby enabling a range of NLP (natural language processing) tasks such as information extraction and question answering. Additionally, by annotating words and expressions with linguistic annotations supervised learning of statistical linguistic parsers is possible.
Previous projects and entities have spent considerable effort to manually annotate English corpora with linguistic annotations. Such annotations have enabled supervised learning of statistical linguistic parsers for English. However, because annotating is generally completed manually, the number of linguistic resources available is greatly reduced, and for most languages these linguistic resources do not exist.